VAT method for visualization of mass movement features : an alternative to hillshaded DEM

Verbovšek, Timotej (avtor), Popit, Tomislav (avtor), Kokalj, Žiga (avtor)

Hillshaded digital elevation models are a well-known information layer used to determine the geomorphological properties of landslides. However, their use is limited because the results are dependent on a particular sun azimuth and elevation. Approaches proposed to overcome this bias include positive openness, sky-view factor, red relief image maps, and prismatic openness. We propose an upgrade to all these methods, a method named Visualization for Archaeological Topography (VAT). The method is based on a fusion of four information layers into a single image (hillshaded terrain, slope, positive openness, and sky-view factor). VAT can be used to enhance visibility of features of varied scale, height, orientation, and form that sit on terrain ranging from extremely flat to very steep. Besides this, the merits of VAT are that the results are comparable across diverse geographical areas. We have successfully tested the method for landslide recognition and analysis in five different areas in the Vipava Valley (SW Slovenia). Geomorphology of the area is very diverse and holds various types of mass movements. In contrast to classical hillshaded digital elevation models (DEMs), the geomorphological features of landslides obtained by the VAT method are very clearly seen in all studied mass movements.

• Jezik: Angleški jezik
• Ključne besede: landslides, geomorphology, VAT, SVF, lidar, aerial laser scanning, Vipava Valley
• Vrsta gradiva: Članek v reviji
• Tipologija: 1.01 - Izvirni znanstveni članek
• Organizacija: NTF - Naravoslovnotehniška fakulteta
• Status publikacije: Objavljeno
• Različica publikacije: Objavljena publikacija
• Leto izida: 2019
• Št. strani: 14 str.
• Številčenje: Vol. 11, iss. 24, art. 2946
• PID: 20.500.12556/RUL-133065
• UDK: 55
• ISSN pri članku: 2072-4292
• DOI: 10.3390/rs11242946
• COBISS.SI-ID: 1529950
• Datum objave v RUL: 10.11.2021

Gradivo je del revije

• Naslov: Remote sensing
• Skrajšan naslov: Remote sens.
• Založnik: MDPI
• ISSN: 2072-4292
• COBISS.SI-ID: 32345133

Licence

• Licenca: CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
• Povezava: http://creativecommons.org/licenses/by/4.0/deed.sl
• Opis: To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.
• Začetek licenciranja: 09.12.2019